Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-fluidsimgit clone --depth 1 https://github.com/AlterLab-IEU/AlterLab-Academic-SkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/alterlab-ieu/alterlab-academic-skills/alterlab-fluidsim)<a href="https://agentmods.dev/skills/alterlab-ieu/alterlab-academic-skills/alterlab-fluidsim"><img src="https://agentmods.dev/badge/skills/alterlab-ieu/alterlab-academic-skills/alterlab-fluidsim/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/alterlab-ieu/alterlab-academic-skills/alterlab-fluidsim"><img src="https://agentmods.dev/badge/skills/alterlab-ieu/alterlab-academic-skills/alterlab-fluidsim.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00078 | $0.02657 |
| Opus 5 | $0.00039 | $0.01328 |
| Sonnet 5 | $0.00016 | $0.00531 |
| Haiku 4.5 | $0.00008 | $0.00266 |
Grade A, and why
alterlab-fluidsim scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 355 lines — stays where its author put it; the contents beside it link to each section on GitHub.
FluidSim
Overview
FluidSim is an object-oriented Python framework for high-performance computational fluid dynamics (CFD) simulations. It provides solvers for periodic-domain equations using pseudospectral methods with FFT, delivering performance comparable to Fortran/C++ while maintaining Python's ease of use.
Key strengths:
- Multiple solvers: 2D/3D Navier-Stokes, shallow water, stratified flows
- High performance: Pythran/Transonic compilation, MPI parallelization
- Complete workflow: Parameter configuration, simulation execution, output analysis
- Interactive analysis: Python-based post-processing and visualization
Core Capabilities
1. Installation and Setup
Install fluidsim using uv with appropriate feature flags:
# Basic installation
uv pip install fluidsim
# With FFT support (required for most solvers)
uv pip install "fluidsim[fft]"
# With MPI for parallel computing
uv pip install "fluidsim[fft,mpi]"
Set environment variables for output directories (optional):
export FLUIDSIM_PATH=/path/to/simulation/outputs
export FLUIDDYN_PATH_SCRATCH=/path/to/working/directory
No API keys or authentication required.
See references/installation.md for complete installation instructions and environment configuration.
2. Running Simulations
Standard workflow consists of five steps:
Step 1: Import solver
from fluidsim.solvers.ns2d.solver import Simul
Step 2: Create and configure parameters
params = Simul.create_default_params()
params.oper.nx = params.oper.ny = 256
params.oper.Lx = params.oper.Ly = 2 * 3.14159
params.nu_2 = 1e-3
params.time_stepping.t_end = 10.0
params.init_fields.type = "noise"
Step 3: Instantiate simulation
sim = Simul(params)
Step 4: Execute
sim.time_stepping.start()
Step 5: Analyze results
sim.output.phys_fields.plot("vorticity")
sim.output.spatial_means.plot()
See references/simulation_workflow.md for complete examples, restarting simulations, and cluster deployment.
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 355 lines · 78 tokens per session scan A bdcc1dd6b6c5
alterlab-fluidsim is a skill published in the GitHub repository AlterLab-IEU/AlterLab-Academic-Skills (66 stars, last pushed 6d ago), licensed MIT. It adds 78 tokens to every session and 2,657 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.
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